tbuckley/cabot-search huggingface dataset:
AI blood signature in common blood tests for detection of gastric cancer in a cohort of 190,000 individuals.
Authors: Tsz Chun Bryan Wong, Serene JL Lam, Ka Man Cheung, Winnie Sung, Peter YM Woo, James CH Chow, Ada SM Yip, Stephen KK Ng, Martin SC Lee, Daisy MY Kan, SS Kao, Harry HY Yiu, David CC Lam
Journal: Journal of Clinical Oncology (2023)

1500 Background: Gastric cancer is the fourth leading cause of cancer death worldwide. Lack of symptoms in the early stage of disease leads to delayed presentation and low overall survival rate. Early detection is key, but there is not yet an established test for non-invasive gastric cancer screening. Routine blood test panels, including complete blood count, liver function, renal function and clotting profiles, could be potentially useful in reflecting bodily processes related to cancer. Current literature and territory-wide statistical data analyses from Hong Kong have shown these subtle changes and differences in measured levels of subcomponents between individuals with and without gastric cancer, that are not recognized clinically, form recognizable patterns distinct to gastric cancer. In this study, we hypothesized that gastric cancer signatures could be identified in routine blood data. Deep learning AI algorithms are used to identify the gastric cancer signature. Results from testing and validation of the identified routine blood signature using a Big Clinical Data cohort are reported. Methods: This is a territory-wide healthcare database study using data from Hong Kong Hospital Authority data collaboration laboratory. All patients prescribed with medications for dyspepsia and with all blood tests components (CBC, LFT, RFT, clotting function) available in the period between 2004-2015 inclusive were included. In the period, data from 2004 to 09 and 2011 to 14 were used as training cohort and the rest were used as testing cohort. A blood gastric cancer signature was generated using deep learning AI algorithms, and applied to predict gastric cancer in Big Data population. Results: 193,117 patients were included in the captioned period, in whom 4,790 patients were diagnosed to have gastric cancer. 151,449 (3,815 pts with gastric cancer and 147,634 pts disease free) patients were included In training cohort. In the testing cohort in 2010 and 2015 (975 pts with gastric cancer and 40,693 pts disease-free), the tumor signature yielded a sensitivity of 0.79, specificity of 0.99, positive predictive value of 0.95 and a negative predictive value of 0.99. Conclusions: The hypothesis of the presence of a distinctive gastric cancer signature from parameters in routine blood test data is tested and validated in a large population cohort with dyspepsia. The signature has high accuracy and high sensitivity with low false positive and false negative rates. Multicenter prospective testing is being conducted in cohort indicated for OGD in Hong Kong.[Table: see text]
Interrogating drug action and immune response in organotypic glioma microenvironment.
Authors: Jiyong Liang, Longfei Huo, Jihong Xu, Pratibha Sharma, Xiaohua Chen, Vinay K. Puduvalli
Journal: Journal of Clinical Oncology (2023)

2068 Background: The glioma tumor microenvironment is characteristic of a high level of heterogeneity and a profoundly immune suppressive phenotype as driven by the presence of glioma stem cells and abundant innate immune cells of the myeloid lineages, rendering glioblastomas (GBM) recalcitrant to conventional treatments and immunotherapies. To address the full complexity of the brain tumor with its diverse components, we have developed an organotypic slice culture system to overcome several limitations of the other preclinical models and allow interrogation of drug action and immunomodulatory agents in human GBM ex vivo. Methods: We performed extensive characterization of the organotypic glioma slice system and optimization of the ex vivo tissue culture conditions, and determined the longitudinal dynamics of slice cell viability, relative tumor versus immune cellularity, and responses to a selection of therapeutic agents and cytokines by multiplexed flow cytometry and single cell transcriptome (scRNA seq) profiling. Results: Single cell transcriptomic analysis showed that both tumor and immune cell heterogeneity were preserved ex vivo for the two-week observation time, which exhibited tumor-type specific gene expression profiles suggesting cooperative interactions among cell populations. Consistent with the findings in fresh tumor specimens and an immune suppressive microenvironment, we found a scarcity of T lymphocytes in IDH mutant gliomas, whereas abundant T cells were found in recurrent GBM slices that persisted ex vivo. Additional analyses revealed that T cell infiltration in GBM was associated with the mesenchymal-like molecular phenotype, which exhibited remarkable intratumor heterogeneity highlighting the presence of stem-like cells and a unique cell population expressing aberrant cancer genes and antigen presenting molecules. We further found that T cells in organotypic GBM slices acquired a potent effector phenotype in response to cytokine-induced reprogramming of microglia and tumor-associated macrophages. In addition, scRNA seq also revealed a population of cancer-associated fibroblast-like cells that are present in all tumors sequenced, which may function to mediate the interactions between immune and tumor cells as our data suggested. Conclusions: We demonstrated that the organotypic slice culture system we developed is compatible with genomic, pharmacological, and immunotherapeutic manipulations and provided data showing that organotypic slice culture preserves glioma microenvironment ex vivo allowing acquisition of crucial information of response of heterogeneous patient tumor tissue to the agent tested. This method represents a unique mechanism by which therapy development can be facilitated in an ex vivo setting.
ERBB2 (HER2) gene amplification concordance analysis of circulating tumor cells and tumor tissue in patients with breast cancer.
Authors: Kay T Yeung, Yipeng Wang, Stephenie Jones, Christopher Brandt, Judy Muller-Cohn, Rolf Muller, Janet Dickerson
Journal: Journal of Clinical Oncology (2023)

e13047 Background: HER2 targeted therapies, such as HER2 monoclonal antibodies, HER2 tyrosine kinase inhibitors, and HER2 antibody drug conjugates, are approved for the treatment of HER2-positive breast, gastric and colorectal cancers. However, inter- and intra-tumoral heterogeneity in HER2 status presented a significant challenge in identifying patients that may benefit from HER2-targeted therapies. Detection of ERBB2 amplification in Circulating Tumor Cells (CTCs) may circumvent tissue heterogeneity issues and effectively predict the response of patients to anti-HER2 agents as a non-invasive alternative approach. Methods: A twenty-four patient pilot study was designed to compare HER2 status of traditional needle biopsies to high sensitivity CTC based liquid biopsies. HER2 status was determined using immunohistochemistry (IHC) and Fluorescence in Situ Hybridization (FISH) for tissue samples and FISH analysis for CTCs. Currently 21 patient samples have been compared in this study. Results: CTCs with HER2 amplified signals were found in patients with stages 2, 3, or 4 breast cancers. Based on the biopsies of the primary tumor or metastatic disease, 6 patients (29%) had HER2-overexpressing as defined by either HER2 IHC 3+ or HER2 FISH amplified. Analysis of CTCs showed 100% concordance (HER2 amplification detected in CTCs) in these patients with HER2-overexpressing breast cancer. Furthermore, an additional 4 (19%) patients had HER2 amplification by CTC analysis but not on needle biopsy. Conclusions: Our finding demonstrates that LiquidScan can be used as a rapid analysis tool to evaluate HER2 amplification in CTCs. This approach can potentially help identify additional cohort of patients (HER2 non-amplified tumor / HER2 amplified CTCs) who may benefit from the new generation of HER2 targeted therapies. Studies are ongoing to include an expanded cohort of patients with early stage disease, as well as HER2-low disease, in order to evaluating dynamics of ERBB2 gene amplification, expression, and pathway activation while on active systemic therapy.
Improvement of the timeliness to lung cancer diagnosis and treatment with the Rapid Access Lung Lesion Clinic in regional Australia.
Authors: Hui Ling Yeoh, Eve Malsem, Benjamin Harrap, Katherine McCann, Wasek Faisal
Journal: Journal of Clinical Oncology (2023)

e13519 Background: The Rapid Access Lung Lesion Clinic (RALLC) was implemented to expedite the multidisciplinary diagnostic pathway of suspected lung cancer in a regional tertiary centre in Victoria, Australia. The aim of this study was to audit the performance of this clinic against the recommended timeframes of the Victorian Optimal Care Pathway for People with Lung Cancer. Methods: Data of all patients referred to the RALLC clinic between July 2017 and December 2021 was prospectively collected, and compared with patients with lung lesions referred to Ballarat Hospital between 2014 to 2015. Information was collected regarding these cohorts’ demographics, cancer care pathway and diagnosis. Results: 302 patients were analysed in this study, of whom, 266 were managed by the RALLC between 2017 to 2021, and 36 patients were managed pre-RALLC between 2014 and 2015. In this cohort, 161 (53%) were males, 256 (85%) were ECOG 0-1 and 251 (83%) had non-small cell lung cancer (NSCLC). 184 (61%) referrals were from general practitioners and 161 (53%) patients received curative-intent treatment. The median time between referral to appointment was 8 days for the RALLC cohort vs. 11 days for the pre-RALLC cohort. The median time between referral to diagnosis was 20 days for the RALLC cohort vs. 36 days for the pre-RALLC cohort. The median time between referral to treatment was 45 days for the RALLC cohort vs. 62 days for the pre-RALLC cohort. The median time between specialist appointment to diagnosis was 11 days for the RALLC cohort vs. 24 days for the pre-RALLC cohort. Conclusions: Although the RALLC did not significantly reduce time between referral to specialist appointment, the clinic did reduce time between referral and specialist appointment to diagnosis, and the time between referral to treatment. The clinic has achieved a marked improvement in meeting the standards of the Optimal Care Pathway for this regional tertiary centre in Australia and demonstrates the benefits of coordinated multidisciplinary service provision especially where specialist access may be limited. Future research is being undertaken to investigate its impact on the clinical outcomes for patients. [Table: see text]
Survival in patients with brain metastasis secondary to breast cancer from Saudi Arabia.
Authors: Atlal M. Abusanad, Omar Iskanderani, Marwan R. Al-hajeili, Reem Ujaimi, Rolina Alwassia
Journal: Journal of Clinical Oncology (2023)

e14018 Background: Breast cancer (BC) is the most common malignancy in women from Saudi Arabia. Nearly one-third of the patients present with metastatic disease. Data on the incidence, pattern and outcome of brain metastasis (BM) in breast cancer patients is yet to be reported to inform the practice and help in assessing the current standard of care. Methods: A retrospective cohort study between the years 2015 and 2020 that included BC patients with BM was conducted. Demographic data, tumor clinico-pathological features, treatment modalities and outcomes were obtained. Survival, factors influencing survival time and the risk of death were examined. A p-value of less than 0.05 was considered statistically significant. Results: 111 patients with BM due to BC were included in the analysis. All are female with a mean age 50.28 ± 11.61 years. IDC histology (93%), grade III (71%), tumor &gt; T2 (64%) and N-positive (60%) BC accounted for the majority. Human epidermal growth factor receptor2 (HER2)-positive/Hormone receptors (HR)-negative was 21%, HER2-positive/HR-positive was 16%, HR-positive/HER2-negative was 31%, TNBC was 22.5% and unknown subtype in 10%. 60% had metastatic disease on presentation with 41% had both skeletal and visceral metastases. Brain lesions &gt; three were reported in nearly half of the cohort. Whole brain radiotherapy (WBRT), surgical resection and SRS were reported in 84%, 16% and 22%, respectively. The mean survival time was 3.31 years with a maximum of 4.23 years and a minimum of 2.39 years. Patients with HR-positive and HER2-positive BC had a significant longer survival (p=0.039, 0.033 respectively). Neither tumor size nor nodal status in BC patients with BM influenced survival time. The presence of visceral metastasesincreased the likelihood of death in BC patients with BM up to 6 folds (p=0.031). The relationship between risk of death, treatment modalities, and response of BM is shown. Conclusions: Although BM secondary to BC represents a therapeutic challenge with an expected unfavorable impact on survival, mortality was associated with the presence of extra-cranial metastases, particularly visceral metastases in this cohort. Longer survival was seen with specific subtypes (HR-positive and HER2-positive), suggesting advancement in systemic treatments against them. [Table: see text]
Genomic landscapes to characterize mismatch-repair deficiency (dMMR)/microsatellite instability-high (MSI-H) gastrointestinal (GI) cancers stratified by tumor mutation burden (TMB).
Authors: Jingyuan Wang, Joanne Xiu, Alex Patrick Farrell, Francesca Battaglin, Hiroyuki Arai, Joshua Millstein, Shivani Soni, Wu Zhang, Anthony F. Shields, Axel Grothey, Benjamin Adam Weinberg, John Marshall, Emil Lou, Moh'd M. Khushman, Davendra Sohal, Michael J. Hall, Matthew James Oberley, David Spetzler, Heinz-Josef Lenz
Journal: Journal of Clinical Oncology (2023)

2618 Background: TMB is a predictive biomarker for immune checkpoint inhibitor treatment in dMMR/MSI-H cancers. We aimed to characterize specific molecular features of a large cohort of dMMR/MSI-H GI tumors with a range of TMB levels. Methods: A total of 2272 GI tumors tested as dMMR/MSI-H were analyzed using Next-generation sequencing (NGS) and immunohistochemistry (IHC) (Caris Life Sciences, Phoenix, AZ). MMR/MSI status was evaluated by a combination of IHC, Fragment Analysis and NGS. TMB-H were defined using differing TMB cutoffs (10, 20, 50 mutations/Mb). Molecular features were compared in four groups (TMB &lt; 10 vs 10-20 vs 20-50 vs ≥50mutations/Mb) using Fisher-Exact or Chi-square and adjusted for multiple comparison by Benjamini-Hochberg. The impact of TMB on tumor immune environment was analyzed using a TCGA cohort. Significance was determined by adjusted (adj) P &lt; 0.05. Results: Tumors with TMB over 10, 20, 50 mutations/Mb were observed in 95.38%, 86.05% and 14.47% respectively in the dMMR/MSI-H GI cohort. Compared to other groups, dMMR/MSI-H GI tumors with TMB over 50 mutations/Mb exhibited the highest mutations rates in RNF43, MSH6, KMT2D, BRCA2 and ASXL1 (Top 5, all P adj &lt; 0.0001). Among the four MMR genes, only MLH1 mutation had no association with higher TMB. The rates of CNNE1 amplification (i.e. the Cycle E1 gene) and HER2 overexpression were the highest in tumors with TMB below 10 mutations/Mb (all P adj &lt; 0.05). The association between PD-L1 positivity and TMB levels was only observed in gastroesophageal cancers ( P= 0.03). The lymphocyte infiltration signature score, IFNγ response and M1 macrophage infiltration were significantly lower, while fraction of genome alterations was significantly increased in dMMR/MSI-H tumors with TMB below 10 mutations/Mb, compared to other subgroups (all P&lt; 0.05). Neoantigens were significantly enriched in those with TMB over 50 mutations/Mb, compared to other subgroups ( P&lt; 0.0001). Conclusions: This is the largest study to investigate the distinct molecular landscape of dMMR/MSI-H GI cancers with different degrees (magnitude) of TMB. These data may inform our understanding of the efficacy of ICB in dMMR/MSI-H GI tumors.
A multicenter retrospective study of the duration of adjuvant temozolomide in IDH-mutant gliomas.
Authors: Isabella Densmore, Tyler Ashford Lanman, Tresa McGranahan
Journal: Journal of Clinical Oncology (2023)

e14048 Background: Gliomas with isocitrate dehydrogenase (IDH) mutations have improved prognosis and are more treatment responsive compared to IDH wild-type gliomas. For glioblastoma (IDH wild-type glioma), Stupp protocol has demonstrated superiority with 6 cycles of adjuvant temozolomide (TMZ). However, recommended duration of TMZ for IDH mutant gliomas is not well-defined, with studies such as RTOG 0424, CATNON, and CODEL extending treatment up to 12 cycles. Prolonged TMZ duration following radiation therapy (RT) is associated with increased toxicity including both financial (cost of drug, lab work, and visits) and drug side effects including cytopenias. We aimed to evaluate for any differences in survival between patients treated with more than 6 cycles of TMZ and those treated with 6 or fewer. Methods: We conducted a multicenter retrospective study of patients treated at the University of Washington and Stanford Medical Center for oligodendrogliomas (oligo) and IDH mutated astrocytomas (astro) using World Health Organization 2016 molecular diagnostic criteria including IDH mutation. Other inclusion criteria were grades 2 and 3, as well as treatment with RT (with or without concurrent TMZ) followed by adjuvant TMZ monotherapy with number of cycles documented. Survival probability, mean overall survival (mOS) and mean progression-free survival (mPFS), were calculated using Kaplan-Meier method with distributions compared using log-rank test in Prism GraphPad comparing &gt;6 cycles of adjuvant TMZ and ≤6 cycles. Results: Of 153 patients treated with both XRT and adjuvant TMZ, 88 were treated with between 1 and 6 cycles of adjuvant TMZ, while 91 were treated with &gt;6 cycles Treatment duration ranged from 1-12 cycles for oligos, 4-12 cycles for grade 2 astros, and 1-14 cycles for grade 3 astros. mOS of oligos was undefined for those treated with 1-6 cycles and 84 months (m) for those treated with &gt;6 cycles (p=0.1448). mOS of grade 2 astros was 154m for those treated with 1-6 cycles and 162.9m for those treated with &gt;6 cycles (p=0.8864). mOS of grade 3 astros was undefined for those treated with 1-6 cycles and 117m for those treated with &gt;6 cycles (p=0.8003). mPFS of oligos was 93m for those treated with 1-6 cycles and undefined for those treated with &gt;6 cycles (p=0.584). mPFS of grade 2 astros was 79.6m for those treated with 1-6 cycles and 144.56m for those treated with &gt;6 cycles (p=0.610). mPFS of grade 3 astros was 72m for those treated with 1-6 cycles and 79.4m for those treated with &gt;6 cycles (p=0.9596). Conclusions: While this study is limited by power, there was no difference in mOS or mPFS with greater than 6 cycles of TMZ among patients with oligodendrogliomas and IDH mutant astrocytomas. More data is needed to evaluate the optimal treatment duration to maximize survival without over-exposing these patients to toxicities.[Table: see text]
Guidance on modeling circulating miRNA to distinguish multiple cancer types by an observation of large-scale open data.
Authors: Jason Chia-Hsun Hsieh, Tsung-Ting Hsieh, Ko-Han Lee, Yu-Chuan Chang
Journal: Journal of Clinical Oncology (2023)

e13537 Background: Cell-free miRNAs (cf-miRNA), circulated in body fluids such as plasma or serum, have shown their ability to detect, diagnose, and monitor cancers. Combining machine learning (ML) technology with these biomarkers facilitates early detection of cancers, which increases the accuracy of clinical decisions and empowers people to take control of their health status. However, the data of the cf-miRNAs has characteristics, which will affect the results of ML. Therefore, this study tries to expound on them in different aspects and to build a reasonable model. Methods: We downloaded large-scale datasets of the platform GPL21263 from the Gene Expression Omnibus for modeling experiments. We curated 8,174 subjects with 2,565 miRNA targets across 7 cancer types of different cf-miRNA-based cancer studies. Moreover, we used principal component analysis (PCA) to observe the datasets, recursive feature elimination (RFE) for feature selection, and tree-based algorithms to build the prediction model. Results: The characteristics of the cf-miRNA we like to share are: (1) Cancer subjects express more cf-miRNAs than control subjects. In the control group, there were 294 and 327 miRNAs with missing rates under 50% and 25%, respectively. In contrast, there were 395 and 485 miRNAs with the same thresholds in the cancer group; (2) Dividing subjects into cancer and control groups is simpler than distinguishing specific cancer types. In the PCA, the average Euclidean distance between the control group and each cancer type is 98.48, while it is 20.23 within each cancer type; (3) For obtaining cancer-specific biomarkers, we suggested that other non-target cancer subjects should be considered as negative controls. We modeled 7 cancer types and compared the proportion of cancer-specific biomarkers, not selected by any other models. The proportion increased from 30.0% to 57.8% after we added other non-target cancer subjects to the control group; next, we focus on multi-cancer modeling: (4) We need at least 400 samples to distinguish seven cancer types. In our experiment, we kept increasing the size of the training data, a hundred at a time. As data was added to the model, the accuracy increased but plateaued after adding 400 samples; (5) Based on RFE, 120 miRNAs is a reasonable number to distinguish seven cancers. Moreover, we found some of these miRNAs are only expressed in cancer subjects. We might lose this kind of biomarkers if we filtered out them by the missing rate; (6) The 10-fold cross validation accuracy of the multi-cancer model can achieve 93.0% using the gradient-boosted trees algorithm. Conclusions: In this study, we showed the guidance for modeling miRNAs in different aspects, including labeling strategy, sample and feature sizes, and the high-accuracy multi-cancer model we can achieve. We hope this guidance would inspire researchers on cf-miRNA-related machine learning applications.